← Cockpit
AI_001predictionAIASI-2030-peak-human

AI will surpass peak human intelligence across ALL economically valuable domains by 2030, extending the sequential maturation roadmap beyond 'independent researcher' (2028) into full-domain superintelligence.

Predictor: Sam Altman

Prior probability
32.0%
Current probability
32.6%
evolves via intake + LBP
Conviction
4/5
Signal quality
A
Resolution
pending
Window
2030-01-01 – 2030-11-30
Edges in / out
5 / 0
Tickers exposed
0

Prediction text

AI will surpass peak human intelligence across ALL economically valuable domains by 2030, extending the sequential maturation roadmap beyond 'independent researcher' (2028) into full-domain superintelligence. | Frontier model expert-level GDPval saturation

Key catalyst: Frontier model expert-level GDPval saturation

Watch events: Frontier model expert-parity benchmarks; GDPval saturation; OpenAI capability disclosures

Resolution evidence

Status: pending

Altman sequential roadmap internally consistent 2023-2026; GPT-6-class capabilities forecast for 2027-2028. Peak-human ASI by 2030 aligns with Aschenbrenner intelligence-explosion framing but aggressive vs Hassabis / Karpathy.

Predictor: Sam Altman

κ + Brier as of 2026-05-22
κ (discount)
0.583
Brier
0.0625
excellent
Hits / Misses
0 / 0
of 1 resolved
Hit rate
0.0%
Calibration plot (stated vs observed)

Evidence about this node from Sam Altman is multiplied by κ in /api/intake. Lower κ = less weight; floors at 0.10 (effectively silenced) and caps at 1.00 (full weight).

Reference class

Not linked

This node isn't linked to a reference class. The Bayesian update applies without outside-view blending.

Probability over time

4 prob_history rows
0%25%50%75%100%prior 32%2026-04-302026-05-032026-05-10
intake v2milestone miss sweeplbp propagationreference class assignedlegacy v1prior_prob (analyst seed)current = 32.6%

Milestone chain

Pre-event signals (upstream prereqs + window checkpoints) → resolution event → downstream cascades. Status/dates update from linked nodes; re-derive nightly via scripts/ops/derive_milestones.py.
Leading chain: 9 pending
  1. 2026-09-01 → 2027-06-30pendingFrontier model crosses 80% on full GDPval gold set across all 9 sectors
    How: GPT-5.4 already 83% per Artificial Analysis; signal is sustained >80% expert-tie-or-win rate across nine sectors with public reproducibility
    Source: https://artificialanalysis.ai/evaluations/gdpval-aaconf 75%
  2. 2027-01-01 → 2028-12-31pendingPublic AI agent autonomously runs an end-to-end biology, chemistry, or ML research project (no human checkpoint > 24h)
    How: Verifiable demonstration: AI agent runs >=14-day continuous research project producing publishable result, with logged human intervention < 24h granularity
    Source: Internal estimate based on Anthropic Claude agent / OpenAI Operator / Sakana AI Scientist trajectoriesconf 45%
  3. 2027-06-01 → 2029-06-30pendingFrontier-lab AI safety institute reports model exhibiting 'beyond peak human' performance in 3+ economically significant domains
    How: US AISI, UK AISI, or METR formal evaluation report identifies superhuman performance (top decile of human experts) in >=3 of {software engineering, mathematical research, drug discovery, financial analysis, legal analysis}
    Source: Internal estimate based on AISI evaluation cadenceconf 50%
  4. 2029-03-31pendingScenario fires: AGI mid: Kurzweil 2029 path
  5. 2028-06-01 → 2030-06-30pendingIndustry expert blind evals show AI win rate >50% across all 44 GDPval occupations
    How: GDPval (or successor) public leaderboard: leading model achieves >50% strict 'win' (not tie) in blind expert review across all 44 occupations
    Source: https://openai.com/index/gdpval/conf 40%
  6. 2029-01-01 → 2030-12-31pendingCascade: Sam Altman publicly declares OpenAI internal model is 'peak human' across all economically valuable domains
    How: Sam Altman public statement (blog, interview, S-1) explicitly claiming a deployed OpenAI model meets or exceeds peak-human bar across all economically valuable domains, paired with red-team evidence
    Source: Internal estimate based on Altman's 2025-2026 'gentle singularity' blog cadenceconf 45%
  7. 2030-02-28pendingQ1 window check-in (25%)
  8. 2030-04-28pendingQ2 window check-in (50%)
  9. 2030-06-25pendingQ3 window check-in (75%)

No downstream cascades — this prediction is a leaf in the dependency graph.

What if this resolves?

Clamp this prediction TRUE or FALSE and run a counterfactual Gibbs sample. Surfaces the predictions whose marginals shift most under that assumption.
(live posterior: 33%)

Click a button to clamp this prediction and run a Gibbs sample. Returns the predictions whose marginals shift most. ~30s per run; ideal for stress-testing "if X resolves, what else moves?"

Evidence chain

Every probability update with full Bayesian provenance — chronological, latest first
LBP2026-05-10T02:00:02Z32.6%+1.2pp
Network propagation: 31.3% → 32.6%
6-iter LBP, residual 0.00584 · damping 0.5, w_intrinsic 0.5 · method lbp_v3 · run e5c18d29
LBP2026-05-03T02:00:01Z31.3%+2.4pp
Network propagation: 29.0% → 31.3%
6-iter LBP, residual 0.00677 · damping 0.5, w_intrinsic 0.5 · method lbp_v3 · run 1a683ac9
LBP2026-04-30T16:39:51Z29.0%-1.0pp
Network propagation: 30.0% → 29.0%
5-iter LBP, residual 0.00825 · damping 0.5, w_intrinsic 0.5 · method lbp_v2 · run 0c8a4ea3
LBP2026-04-30T02:18:57Z30.0%-2.0pp
Network propagation: 32.0% → 30.0%
5-iter LBP, residual 0.00825 · damping 0.5, w_intrinsic 0.5 · method lbp_v1 · run 592311ef

Network propagation neighbors

Top edges sorted by latest LBP cross-impact
All propagation →

Top incoming (parents)

Edges that influence THIS node's belief

KindNodeTheir probP(c|s=T)P(c|s=F)Δ implied
killerTK01
AGI Capability Plateau (2026-27 Training Stall)
15.0%0.0500.320-0.046

Top outgoing (children)

Predictions THIS node influences

No outgoing edges.

Prerequisites (5)

Predictions that must hit first
TypePredTitleDomainLag
correlateS_AGI_MID_2029AGI mid: Kurzweil 2029 pathagi_general_capability
correlateS_AGI_FAST_2027AGI fast: drop-in remote worker by 2027-09agi_general_capability
correlateS_NO_RECESSION_5YNo NBER recession through 2031macro_recession
correlateS_AGI_WINTER_2036PLUSAGI delayed: capability plateau or AI winteragi_general_capability
killerTK01AGI Capability Plateau (2026-27 Training Stall)

Dependents (0)

Predictions enabled by this
TypePredTitleDomainLag
No dependents

Linked documents (6)

Auto-generated by cosine similarity from Polymarket / Manifold / EDGAR / GDELT
SimSourceTitleMarket probPolarityReviewedPublished
0.724manifoldGlobal AI Diffusion Rate ≥ [X]% by End of Q4 2026mentionspending2026-05-14
0.704manifoldWhen will global population peak?mentionspending2026-05-06
0.675manifoldWill there be a publicly explicated Scientific Theory of Deep Learning before 2032?41%mentionspending2026-05-02
0.617arxivUnsupervised Machine Learning for Detecting Structural Anomalies in European Regional Statisticsmentionspending2026-05-04
0.586manifoldWill Poland surpass the UK in GDP per capita by PPP prior to 2035?42%mentionspending2026-04-26
0.566manifoldWill The Democrats Win Every Presidential Election from 2028 to 2040?11%mentionspending2026-05-29

Raw metadata

From Thesis_Timeline_v1.0_FINAL workbook
{
  "nia": false,
  "qty": "peak-human ASI",
  "mode": "FORECAST",
  "role": "Cited-CEO",
  "context": "Extends Altman's prior intern-by-2026 (CMQ_001) / researcher-by-2028 (CMQ_002) sequential-maturation framing into ASI tier. Altman has also publicly distanced OpenAI from the term 'AGI' as 'not a super useful term' due to definitional ambiguity.",
  "to_year": 2030,
  "conv_cues": "CEO FIRST_PERSON; explicit year; deterministic scaling-law framing",
  "direction": "HAPPEN",
  "from_year": 2030,
  "timeframe": "by 2030",
  "conv_level": "HIGH",
  "milestones": [
    {
      "kind": "llm_pre_event",
      "label": "Frontier model crosses 80% on full GDPval gold set across all 9 sectors",
      "source": "https://artificialanalysis.ai/evaluations/gdpval-aa",
      "status": "pending",
      "weight": 0.4,
      "ordinal": -9,
      "source_id": null,
      "confidence": 0.75,
      "source_url": "https://openai.com/index/gdpval/",
      "expected_date": "2027-01-30",
      "research_origin": "training",
      "expected_date_range": {
        "to": "2027-06-30",
        "from": "2026-09-01"
      },
      "measurement_criterion": "GPT-5.4 already 83% per Artificial Analysis; signal is sustained >80% expert-tie-or-win rate across nine sectors with public reproducibility"
    },
    {
      "kind": "llm_pre_event",
      "label": "Public AI agent autonomously runs an end-to-end biology, chemistry, or ML research project (no human checkpoint > 24h)",
      "source": "Internal estimate based on Anthropic Claude agent / OpenAI Operator / Sakana AI Scientist trajectories",
      "status": "pending",
      "weight": 0.4,
      "ordinal": -8,
      "source_id": null,
      "confidence": 0.45,
      "expected_date": "2028-01-01",
      "research_origin": "training",
      "expected_date_range": {
        "to": "2028-12-31",
        "from": "2027-01-01"
      },
      "measurement_criterion": "Verifiable demonstration: AI agent runs >=14-day continuous research project producing publishable result, with logged human intervention < 24h granularity"
    },
    {
      "kind": "llm_pre_event",
      "label": "Frontier-lab AI safety institute reports model exhibiting 'beyond peak human' performance in 3+ economically significant domains",
      "source": "Internal estimate based on AISI evaluation cadence",
      "status": "pending",
      "weight": 0.4,
      "ordinal": -7,
      "source_id": null,
      "confidence": 0.5,
      "expected_date": "2028-06-15",
      "research_origin": "training",
      "expected_date_range": {
        "to": "2029-06-30",
        "from": "2027-06-01"
      },
      "measurement_criterion": "US AISI, UK AISI, or METR formal evaluation report identifies superhuman performance (top decile of human experts) in >=3 of {software engineering, mathematical research, drug discovery, financial analysis, legal analysis}"
    },
    {
      "kind": "scenario_signal",
      "label": "Scenario fires: AGI mid: Kurzweil 2029 path",
      "status": "pending",
      "weight": 0.7,
      "ordinal": -6,
      "source_id": "S_AGI_MID_2029",
      "expected_date": "2029-03-31",
      "observed_date": null
    },
    {
      "kind": "llm_pre_event",
      "label": "Industry expert blind evals show AI win rate >50% across all 44 GDPval occupations",
      "source": "https://openai.com/index/gdpval/",
      "status": "pending",
      "weight": 0.4,
      "ordinal": -5,
      "source_id": null,
      "confidence": 0.4,
      "expected_date": "2029-06-15",
      "research_origin": "training",
      "expected_date_range": {
        "to": "2030-06-30",
        "from": "2028-06-01"
      },
      "measurement_criterion": "GDPval (or successor) public leaderboard: leading model achieves >50% strict 'win' (not tie) in blind expert review across all 44 occupations"
    },
    {
      "kind": "llm_post_event",
      "label": "Cascade: Sam Altman publicly declares OpenAI internal model is 'peak human' across all economically valuable domains",

... (truncated)